Today, Amazon Web Services announces that Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML is available for P5 instances in two new regions: US West (Oregon) and Asia Pacific (Tokyo). You can use EC2 Capacity Blocks to reserve highly sought-after GPU instances in Amazon EC2 UltraClusters for a future date for the amount of time that you need to run your machine learning (ML) workloads.
EC2 Capacity Blocks enable you to reserve GPU capacity up to eight weeks in advance for durations up to 28 days in cluster sizes of one to 64 instances (512 GPUs), giving you the flexibility to run a broad range of ML workloads. They are ideal for short duration pre-training and fine-tuning workloads, rapid prototyping, and for handling surges in inference demand. EC2 Capacity Blocks deliver low-latency, high-throughput connectivity through colocation in Amazon EC2 UltraClusters.
With this expansion, EC2 Capacity Blocks for ML are available for the following instance types and AWS Regions: P5 instances in US East (N. Virginia), US East (Ohio), US West (Oregon), and Asia Pacific (Tokyo); P5e instances in US East (Ohio); P4d instances in US East (Ohio) and US West (Oregon); Trn1 instances in Asia Pacific (Melbourne).
To get started, visit the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs. To learn more, see the Amazon EC2 Capacity Blocks for ML User Guide.
Source:: Amazon AWS